Python avanzado: NumPy y Pandas

Name: Python avanzado: NumPy y Pandas
Author: Jeremy Kurtz

Este curso le enseñará sobre la biblioteca NumPy y la herramienta Pandas en Python. NumPy es una biblioteca principal de Python. La herramienta Pandas es un…

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In this lesson and the next several lessons, we are going to be working with the NumPy library. We will also be working with the Pandas library and we're going to be working with arrays. The reason for this is we've reached a point where the power associated with Python is going to be realized and that realization comes in the form of data. So the first thing we have to make sure of is that we have the correct libraries installed on our Python distribution. So the way to do that is to open up a command prompt by typing a cmd and when it opens up the command prompt, we're going to go ahead and install the libraries that we need. Now I have the libraries already installed, so mine's going to go a little bit quicker than yours. However, it will work just the same and it's just as easy. So the first thing we're going to do is we're going to type pip install and then N U M P Y for NumPy hit enter and it will go through the process on your machine saying that it needs to be installed. But on my machine, since it's already installed, it says the requirement is already satisfied. Next, we're going to do the exact same thing for pandas. So we have pip install NumPy and we're going to take out NumPy and type in pandas, like the animals. We will hit enter again. And it will go through and check all the requirements. It will check everything to make sure that you have all the necessary files that pandas works off of installed. And if you don't, it will actually install those for you. So at this point, we have them installed. And if we want to test them, what we can do is close our window after the installation is made, open up our idle environment. And what I'm going to do is start a new file. And I'm going to call this file test. So file save as. And on our desktop, we have our advanced Python folder. And I'm going to say this as num test. Once that's done, we can type import NumPy. And we're going to do it a little bit different because we're going to use so many functions in this library, we're going to go ahead and give it a name. So we will just call it NP for NumPy. And what we're going to do is save this. And run it. And you'll notice we don't actually see anything happen. However, what we do see is we see that there are no errors. So this is the first step. Now what we're going to do is we're going to do the exact same thing using the pandas library. We're going to import pandas as PD. Now if I save it and run it again, hopefully, I won't have an error. And now I know that both libraries are set up correctly. In the event that you get an error, the error is generally caused by a path issue. So the best thing to do is to append your advanced Python directory to your path. Now I'm not going to show how to do that. And the reason for that is that when you work inside your path and your environment variables, it is not a very safe place to be. Because there are things you can do that could cause a problem. The other thing you can do if you do not want to go through that process and it's not hard. You can also move your advanced Python directory or the files in it to where your Python executable is. So there we have it. In our next lesson, we are going to make a basic data grid. See you then.

Avanzado Proveedor : Jeremy Kurtz 8 lecciones · 42m en Árabe, Alemán, Inglés, Español, Francés, Portugués, Chinese

Descripción del curso

Este curso le enseñará sobre la biblioteca NumPy y la herramienta Pandas en Python. NumPy es una biblioteca principal de Python. La herramienta Pandas es un medio de análisis y manipulación de datos de código abierto rápido, potente, flexible y fácil de usar.

Lo que aprenderás

Entender la biblioteca NumPy en Python
Usar la herramienta Pandas para análisis y manipulación de datos
Trabajar con arreglos usando NumPy
Clasificar arreglos con NumPy
Buscar arreglos con NumPy
Usar Pandas con archivos CSV

Puntos clave

NumPy es una biblioteca principal de Python cubierta en este curso.
Pandas es una herramienta de código abierto rápida, poderosa, flexible y fácil de usar para análisis y manipulación de datos.
El curso cubre trabajar con arreglos en NumPy, incluyendo usar, clasificar y buscar arreglos.
El curso muestra cómo usar Pandas con archivos CSV.

Preguntas frecuentes

¿Qué cubre este curso?

Este curso enseña la biblioteca NumPy y la herramienta Pandas en Python, incluyendo usar, clasificar y buscar arreglos con NumPy y trabajar con Pandas y archivos CSV.

¿Qué aprenderé a hacer con Pandas?

Aprenderás a usar Pandas, una herramienta de código abierto rápida, poderosa, flexible y fácil de usar, para análisis y manipulación de datos, incluyendo trabajar con archivos CSV.

¿Qué habilidades construye este curso?

Construye habilidades en NumPy, Pandas y Python, junto con ScientificPython, Scikit-Learn y SciPy.

¿Es NumPy una parte importante de este curso?

Sí. NumPy se describe como una biblioteca principal de Python y el curso cubre entender NumPy y usarlo para trabajar con, clasificar y buscar arreglos.